The International Conference on Computational creativity is soliciting
proposals for workshops to be held along with the main ICCC conference. We
welcome proposals for half-day, full-day and one-and-a-half day workshops
on any aspect of computational creativity research. Workshops offer a great
opportunity to exchange ideas, and a chance to drive broader adoption of
your systems and methods. We welcome a diversity of formats, such as
academic workshops (with a process of peer-review for submitted papers) or
hands-on, practical workshops. Please feel free to contact the organisers
to discuss the possibilities further. All workshops will be academically
self-contained: they should have their own organising committee and conduct
their own peer-review and publication process where necessary.
**** Important dates ****
Workshop proposal submissions due: February 10th, 2020.
Workshop organisers are also encouraged to submit their proposals earlier
than the deadline and request an earlier response in order to allow more
time for their own submission process.
Notification of workshop acceptance: February 24th, 2019.
(Earlier acceptance may be possible at the chairs’ discretion, to allow
workshops a longer lead-time).
Note: all workshops should manage their own paper submission, review and
publication process, with appropriate timelines.
**** Submission Instructions ****
Please submit a PDF proposal of no more than 3 pages detailing the
– Title and theme of workshop;
– Description of the workshop’s scope and the type of papers and/or works
that will be accepted (feel free to refer to previous instances of the
workshop, including publications);
– Expected duration, number of participants, format and rough event
schedule (duration can be half-day, full-day or one-and-a-half-day);
– Any technical or space requirements (e.g., projector, PA, whiteboards);
– Details of your workshop timeline;
– Preliminary organising committee.
– Details of any invited speakers, if known at the time of submission
Dear Colleagues, Friends of IK and any Curious Minds,
as the co-chairs for the Interdisciplinary College (IK) 2020 spring school, we are excited to announce that the programme for the event is now complete and that the registration is open.
In case you have not heard about it, IK is an annual one-week spring school, which offers a dense, intensive, and state-of-the-art course program in neurobiology, neural computation, cognitive science, artificial intelligence, and related areas. It is aimed at graduate students, postgraduates, and researchers from academia and industry. By combining humanities, science, and technology, the unique event aims to intensify dialogue between – and connectedness of – researchers in the various disciplines.
IK 2020 will take place in Günne at Lake Möhnesee in Germany (near Dortmund) from March 13 to 20, next year. The deadline for early bird registrations is January 7th, 2020.
The focus theme will be *Curiosity, Risk & Reward: Shaping Autonomous Intelligence*. Curiosity is an exciting, yet comparatively underexplored interdisciplinary research topic that is currently seeing growing interest from many areas, including artificial intelligence, decision making, robotics, as well as learning and development in biological systems.
The diverse program will include introductory, focused, as well as practical courses and more.
As selected highlights, we will be able to host evening lectures by:
Celeste Kidd, University of California, Berkeley
Bing Brunton, University of Washington, Seattle
Alex Kacelnik, Oxford University
Tanja Schultz, Universität Bremen
Computational Creativity (or CC) is a discipline with its roots in
Artificial Intelligence, Cognitive Science, Engineering, Design, Psychology
and Philosophy that explores the potential for computers to be autonomous
creators in their own right. ICCC is an annual conference that welcomes
papers on different aspects of CC, on systems that exhibit varying degrees
of creative autonomy, on frameworks that offer greater clarity or
computational felicity for thinking about machine (and human) creativity,
on methodologies for building or evaluating CC systems, on approaches to
teaching CC in schools and universities or to promoting societal uptake of
CC as a field and as a technology, and so on.
**** Themes and Topics ****
Original research contributions are solicited in all areas related to
Computational Creativity research and practice, including, but not limited
– Applications that address creativity in specific domains such as music,
language, narrative, poetry, games, visual arts, graphic design, product
design, architecture, entertainment, education, mathematical invention,
scientific discovery, and programming.
– Applications and frameworks that allow for co-creativity between humans
and machines, in which the machine is more than a mere tool and takes on
significant creative responsibility for itself.
– Metrics, frameworks, formalisms and methodologies for the evaluation of
creativity in computational systems, and for the evaluation of how systems
are perceived in society.
– Syntheses of AI/CC treatments of very different genres or domains of
creativity (e.g. art and science, humour and mathematics, language and
– Computational paradigms for understanding creativity, including heuristic
search, analogical and meta-level reasoning, and representation.
– Resource development and data gathering/knowledge curation for creative
systems, especially resources and data collections that are scalable,
extensible and freely available as open-source materials.
– Ethical considerations in the design, deployment or testing of CC
systems, as well as studies that explore the societal impact of CC systems.
– Cognitive and psychological computational models of creativity, and their
relation with existing cognitive architectures and psychological accounts
– Innovation, improvisation, virtuosity and related pursuits investigating
the production of novel experiences and artefacts within a CC context.
– Computational accounts of factors that enhance creativity, including
emotion, surprise(unexpectedness), reflection, conflict, diversity,
motivation, knowledge, intuition, reward structures.
– Computational models of social aspects of creativity, including the
relationship between individual and social creativity, diffusion of ideas,
collaboration and creativity, formation of creative teams, and creativity
in social settings.
– Perspectives on computational creativity which draw from philosophical
and/or sociological studies in a context of creative intelligent systems.
– Computational creativity in the cloud, including how web services can be
used to foster unexpected creative behaviour in computational systems.
– Big data approaches to computational creativity.
– Debate papers that raise new issues or reopen seemingly settled ones.
Provocations that question the foundations of the discipline or throw new
light on old work are also welcome.
Papers on computational paradigms of all kinds – from symbolic to
statistical to deep learning models, as well as hybrid approaches – are
welcome, provided they address pertinent aspects of CC as sketched above.
**** Paper Types ****
We welcome the submission of five different types of papers: Technical
papers, System or Resource description papers, Study papers, Cultural
application papers and Position papers.
**** Important Dates ****
Submissions due: March 1, 2020
Acceptance notification: April 20, 2020
Camera-ready copies due: May 22, 2020
Conference: June 29 – July 03, 2020
**** More Information ****
More information on the paper types and submission process can be found at
We are happy to announce the fifth Groningen Spring School on Cognitive Modeling (March 30 to April 3, 2020). This year, the Spring School will again cover four different modeling paradigms: ACT-R, Nengo, PRIMs, and error-driven learning. It thereby offers a unique opportunity to learn the relative strengths and weaknesses of these approaches.
Moreover, this year we are offering a lecture series on dynamical systems, which should be interesting for anyone looking into modeling cognitive dynamics at some level of abstraction. We recommend this lecture series as an excellent combination with Nengo, for those interested in neuromorphic computing.
The first day will provide an introduction to all five topics. From day two, spring school students will be asked to commit to one topic, for which they will attend lectures as well as tutorials. In addition, students can sign up for a second topic, for which they will attend lectures only. All students are invited to join a series of plenary research talks on the different paradigms.
On the first day, spring school students are asked to introduce themselves and their research interests in a poster session.
ACT-R is a high-level cognitive theory and simulation system for developing cognitive models for tasks that vary from simple reaction time experiments to driving a car, learning algebra, and air traffic control. ACT-R can be used to develop process models of a task at a symbolic level. Participants will follow a compressed five-day version of the traditional summer school curriculum. We will also cover the connection between ACT-R and fMRI.
Nengo is a toolkit for converting high-level cognitive theories into low-level spiking neuron implementations. In this way, aspects of model performance such as response accuracy and reaction times emerge as a consequence of neural parameters such as the neurotransmitter time constants. It has been used to model adaptive motor control, visual attention, serial list memory, reinforcement learning, Tower of Hanoi, and fluid intelligence. Participants will learn to construct these kinds of models, starting with generic tasks like representing values and positions, and ending with full production-like systems. There will also be special emphasis on extracting various forms of data out of a model, such that it can be compared to experimental data.
How do people handle and prioritize multiple tasks? How can we learn something in the context of one task, and partially benefit from it in another task? The goal of PRIMs is to cross the artificial boundary that most cognitive architectures have imposed on themselves by studying single tasks. It has mechanisms to model transfer of cognitive skills, and the competition between multiple goals. In the tutorial we will look at how PRIMs can model phenomena of cognitive transfer and cognitive training, and how multiple goals compete for priority in models of distraction.
Teachers: Jacolien van Rij and Dorothée Hoppe (University of Groningen)
Error-driven learning (also called discrimination learning) allows to simulate the time course of learning. It is based on the Rescorla-Wagner model (Rescorla & Wagner, 1972) for animal cognition, which assumes that learning is driven by expectation error, instead of behaviorist association (Rescorla, 1988). The equations formulated by Rescorla and Wagner have been used to investigate different aspects of cognition, including language acquisition (e.g., Hsu, Chater, and Vitányi, 2011; St. Clair, Monaghan, and Ramscar, 2009), second language learning (Ellis, 2006), and reading of complex words (Baayen et al, 2011). Although error-driven learning can be applied for all domains in cognitive science, in this course we will focus on how it could be used for modeling language processing and language learning.
Dynamical Systems: a Navigation Guide
Teacher: Herbert Jaeger (University of Groningen)
This lecture-series gives a broad overview over the zillions of formal models and methods invented by mathematicians and physicists for describing “dynamical systems”. Here is a list of covered items: Finite-state automata with and without input, deterministic and non-deterministic, probabilistic), hidden Markov models and partially observable Markov decision processes, cellular automata, dynamical Bayesian networks, iterated function systems, ordinary differential equations, stochastic differential equations, delay differential equations, partial differential equations, (neural) field equations, Takens’ theorem, the engineering view on “signals”, describing sequential data by grammars, Chomsky hierarchy, exponential and power-law long-range interactions, attractors, structural stability, bifurcations, phase transitions, topological dynamics, nonautonomous attractor concepts. In the lectures, I try to work out the underlying connecting lines between the “dots” listed above.
The Faculty of Humanities and Social Sciences at the University of Luxembourg is organizing an International Conference on “The Humanities and the Rise of AI: Implications of Cultural and Societal Engineering” that will take place from 14 to 18 June 2020. The conference is the second part of the series “The Ends of the Humanities”.
Many current discussions on AI are caught up in the attempt to balance questions of what can be done with what should be done. We want to initiate an interdisciplinary conversation that goes beyond this horizon and focuses on the structural changes AI has the potential to bring about – whether we want it or not.
We heartily invite you to share the attached CfP with your members. Thank you very much!
With kind regards,
___________ Dr. Isabell Eva Baumann
University of Luxembourg Campus Belval Maison des Sciences Humaines 11, Porte des Sciences L-4366 Esch-sur-Alzette Luxembourg
Call for papers for the EvoStar conference
(Apologies for cross-posting)
****** NEWS *****
. Due to a large number of requests for late submissions, the EvoStar
submission websites will stay open until Friday, November 15!
Authors who have already submitted, can update their work until this time.
. New webpage for evostar2020 is now online, bookmark it!
*** Overview ***
EvoStar comprises of four co-located conferences run each spring at
different locations throughout Europe. These events arose out of
workshops originally developed by EvoNet, the Network of Excellence in
Evolutionary Computing, established by the Information Societies
Technology Programme of the European Commission, and they represent a
continuity of research collaboration stretching back over 20 years.
EvoStar is organised by SPECIES, the Society for the Promotion of
Evolutionary Computation in Europe and its Surroundings. This
non-profit academic society is committed to promoting evolutionary
algorithmic thinking, with the inspiration of parallel algorithms
derived from natural processes. It provides a forum for information
Topics to be covered include, but are not limited to:
Innovative applications of GP, Theoretical developments, GP
performance and behaviour, Fitness landscape analysis of GP,
Algorithms, representations and operators for GP, Search-based
software engineering, Genetic improvement programming, Evolutionary
design, Evolutionary robotics, Tree-based and Linear GP, Graph-based
and Grammar-based GP, Evolvable hardware, Self-reproducing programs,
Multi-population GP, Multi-objective GP, Parallel GP, Probabilistic
GP, Object-orientated GP, Hybrid architectures including GP,
Coevolution and Modularity in GP, Semantics in GP, Unconventional GP,
Automatic software maintenance, Evolutionary inductive programming,
Evolution of automata or machines.
EvoApplications, the International Conference on the Applications of
Evolutionary Computation -formerly known as EvoWorkshops- brings
together researchers in a variety of areas of application of
Evolutionary Computation and other Nature-inspired techniques.
EvoApplications solicits high-quality original research papers
(including significant work-in-progress) on any aspect of applications
of Evolutionary Computation, both to real-world or methodological
contexts in which Evolutionary Computation can contribute to pushing
the limits of the state of the art beyond the present ones.
In addition to the regular session, 6 special sessions will be
organized on the following topics:
– BioSocNet – Applications of Bio-inspired techniques on Social Networks
– Evolutionary Computation in Digital Healthcare and Personalized Medicine
– Special Session on Soft Computing applied to Games
– Applications of Deep Bioinspired Algorithms
– Distributed and Parallel Systems
– Evolutionary Machine Learning
Which include the following topics:
Applications of metaheuristics to combinatorial optimisation problems,
Representation techniques, Practical solution of NP-hard problems,
Neighbourhoods and efficient algorithms for searching them, Variation
operators for stochastic search methods, Theoretical developments,
Constraint-handling techniques, Parallelisation and grid computing,
Search space and landscape analyses, Comparisons between different
(also exact) methods, Heuristics, Genetic programming and Genetic
algorithms, Tabu search, iterated local search and variable
neighbourhood search, Ant colony optimisation, Artificial immune
systems, Scatter search, Particle swarm optimisation, Memetic
algorithms, Hybrid methods and hybridisation techniques, Matheuristics
(hybrids of exact and heuristic methods), Hyper-heuristics and
autonomous search, Automatic algorithm configuration and design,
Metaheuristics and machine learning, Surrogate-model-based methods,
Estimation of distribution algorithms, String processing, Scheduling
and timetabling, Network design, Vehicle routing, Graph problems,
Satisfiability, Packing and cutting problems, Energy optimisation
problems, Multi-objective optimisation, Search-based software
Which include the following topics and subtopics:
Systems that create drawings, images, animations, sculptures, poetry,
text, designs, webpages, buildings, etc.; Systems that create musical
pieces, sounds, instruments, voices, sound effects, sound analysis,
etc.; Systems that create artefacts such as game content,
architecture, furniture, based on aesthetic and functional criteria;
Robotic-Based Evolutionary Art and Music; Other related artificial
intelligence or generative techniques in the fields of Computer Music,
Computer Art, etc.
Computational Aesthetics, Experimental Aesthetics; Emotional Response,
Surprise, Novelty; Representation techniques; Surveys of the current
state-of-the-art in the area; identification of weaknesses and
strengths; comparative analysis and classification; Validation
methodologies;Studies on the applicability of these techniques to
related areas; New models designed to promote the creative potential
of biologically inspired computation.
.Computer Aided Creativity and Computational Creativity
Systems in which computational intelligence is used to promote the
creativity of a human user; New ways of integrating the user in the
evolutionary cycle; Analysis and evaluation of: the artistic potential
of biologically inspired art and music; the artistic processes
inherent to these approaches; the resulting artefacts; Collaborative
distributed artificial art environments.
Techniques for automatic fitness assignment; Systems in which an
analysis or interpretation of the artworks is used in conjunction with
computational intelligence techniques to produce novel objects;
Systems that resort to computational intelligence approaches to
perform the analysis of image, music, sound, sculpture, or some other
types of artistic object or resource.
*** Important Dates, Venue and Publication ***
Extended! Submission Deadline: November 15, 2019
Conference: April 15-17, 2020
Venue: Seville, Spain
All accepted papers will be printed in the proceedings published by
Springer Verlag in the Lecture Notes in Computer Science (LNCS)
[EXTENDED DEADLINE] Call for papers for the 9th International
Conference on Artificial Intelligence in Music, Sound, Art and Design
(Apologies for cross-posting)
The 9th International Conference on Artificial Intelligence in Music,
Sound, Art and Design (EvoMUSART) will be held in Seville, Spain, on
15-17 April 2020, as part of the evo* event.
SPECIAL ISSUES: There are two special issues on JCR journals
associated to EvoMUSART: “Neural Computing and Applications” (Q1, IF:
4.66) and “Entropy” (Q2, IF: 2.419). See EvoMUSART 2020 webpage for
more information on these special issues.
The main goal of EvoMUSART is to bring together researchers who are
using Artificial Intelligence techniques (e.g. artificial neural
network, evolutionary computation, swarm, cellular automata, alife)
for artistic tasks such as visual art, music, architecture, video,
digital games, poetry, or design. The conference gives researchers in
the field the opportunity to promote, present and discuss ongoing work
in the area.
Accepted papers will be published by Springer Verlag in the Lecture
Notes in Computer Science series.
Extended! Submission deadline: 15 November 2019
Evo*: 15-17 April 2020
We welcome submissions which use Artificial Intelligence techniques in
the generation, analysis and interpretation of art, music, design,
architecture and other artistic fields. Submissions must be at most 16
pages long, in Springer LNCS format. Each submission must be
anonymised for a double-blind review process. The deadline for
submission is 1 November 2019. Accepted papers will be presented
orally or as posters at the event and included in the EvoMUSART
proceedings published by Springer Verlag in a dedicated volume of the
Lecture Notes in Computer Science series.
Indicative topics include but are not limited to:
* Systems that create drawings, images, animations, sculptures,
poetry, text, designs, webpages, buildings, etc.;
* Systems that create musical pieces, sounds, instruments, voices,
sound effects, sound analysis, etc.;
* Systems that create artefacts such as game content, architecture,
furniture, based on aesthetic and/or functional criteria;
* Systems that resort to artificial intelligence to perform the
analysis of image, music, sound, sculpture, or some other types of
* Systems in which artificial intelligence is used to promote the
creativity of a human user;
* Theories or models of computational aesthetics;
* Computational models of emotional response, surprise, novelty;
* Representation techniques for images, videos, music, etc.;
* Surveys of the current state-of-the-art in the area;
* New ways of integrating the user in the process (e.g. improvisation,
Mensch und Technik arbeiten in Zukunft immer enger zusammen. Umso wichtiger wird es künftig, dass der Mensch mit seinen individuellen Bedürfnissen und Fähigkeiten bei der Interaktion mit Maschinen oder Software optimal unterstützt wird. Dabei helfen neuroadaptive Technologien.
Das Fraunhofer IAO lädt Sie herzlich dazu ein, die Einsatzmöglichkeiten und Potenziale dieses neuen Forschungsgebiets kennenzulernen bei der Veranstaltung:
“Interaktion mit Hirn”
am 27. November 2019 in Stuttgart
Erfahren Sie in verschiedenen Veranstaltungsformaten, inwiefern Unternehmen aller Branchen von den Entwicklungen im Bereich neuroadaptiver Technologien profitieren können. Die Fachvorträge vereinen Perspektiven aus Forschung und Wirtschaft.
Finden Sie u.a. heraus, welche Potenziale neuroadaptive Systeme für das Lernen haben (Dr. Maria Wirzberger, Max-Planck-Institut für Intelligente Systeme), ob Maschinen Emotionen empfinden können (Eileen Baum, Noldus Information Technology) und diskutieren Sie in einem interaktiven Workshop gemeinsam über Herausforderungen und mögliche Lösungsansätze.
(Apologies for cross-posting)
The Special Session on Evolutionary Machine Learning (EML) of Evo Apps
will provide a specialized forum of discussion and exchange of
information for researchers interested in exploring approaches that
combine nature and nurture, with the long-term goal of evolving
Artificial Intelligence (AI).
Giving response to the growing interest in the area, and consequent
advances of the state-of-the-art, the special session covers
theoretical and practical advances on the combination of Evolutionary
Computation (EC) and Machine Learning (ML) techniques.
Topics of interest include, but are not limited to:
– EC as an ML technique: Using EC to solve typical ML tasks such as
Classification or Clustering
– EC applied ML algorithms: Neuroevolution, Feature Selection, Feature
Engineering, Evolutionary Adversarial Models
– ML applied to EC: Surrogate-model design by ML for EC, Learning
Problem Structure, ML for Diversity, Designing Search Strategies,
Predicting Promising Regions, Using ML to Decrease Computational
– Real world applications issues: EC for Fairness, Robustness,
Trustworthiness and Explainability; Green EML
– Emerging topics: EC for AutoML; EC for Transfer Learning; EC for
Multitasking; Evolving Learning Functions, Neurons and Linkage; EC for
Verification and Validation of ML
Submission deadline: 1 November 2019
Evo*: 15-17 April 2020
Submissions must be original and not published elsewhere. They will be
peer reviewed by members of the program committee. The reviewing
process will be double-blind, so please omit information about the
authors in the submitted paper. Submit your manuscript in Springer
LNCS format and provide up to five keywords in your Abstract.
The Immersive Learning Research Network (iLRN) is a burgeoning global network of researchers and practitioners collaborating to develop the scientific, technical, and applied potential of immersive learning. Its annual conference is the premier scholarly event focusing on advances in the use of virtual reality (VR), augmented reality (AR), mixed reality (MR), and other extended reality (XR) technologies to support learners and learning. Leading scholars and professionals operating in formal education settings as well as those representing diverse industry sectors will converge on the historic and picturesque coastal city of San Luis Obispo, California for iLRN 2020, where they will share their research findings, experiences, and insights; network and establish partnerships to envision and shape the future of XR and immersive technologies for learning; and contribute to the emerging scholarly knowledge base on how these technologies can be used to create experiences that educate, engage, and excite learners.
##### SESSSION TYPES & SESSION FORMATS #####
*** Academic Stream ***
(Refereed papers for proceedings)
– Full or short paper for oral presentation
– Short or work-in-progress paper for poster presentation
– Work-in-progress paper for doctoral colloquium
*** Practitioner Stream ***
(No paper – refereed on the basis of abstract)
– Oral presentation
– Poster presentation
– Demo showcase
*Full and short papers can only be submitted in the main round.
##### PUBLICATION & INDEXING #####
Accepted and registered papers presented at iLRN 2020 will be published in the conference proceedings and submitted to the IEEE Xplore® digital library. IEEE makes Xplore content available to its abstracting & indexing partners, including Elsevier (Scopus, Ei Compendex) and Clarivate Analytics (CPCI – part of Web of Science).